class_docstr: Cifar10 dataset with CNN network model.
code: def __init__(
      self,
      nnObj,
      is_training,
      batch_norm_decay,
      batch_norm_epsilon,
      data_format="channels_first",
  ):
      super(ConvNetCifar10, self).__init__(
          is_training, data_format, batch_norm_decay, batch_norm_epsilon
      )
      self.num_classes = 10 + 1
      self.nnObj = nnObj
  
file_path: dragonfly/examples/nas/cg/cifar/cifar10_model.py
imports: from __future__ import division
  from __future__ import print_function
  import tensorflow
  from cifar10_model_base import ConvNet
label_desc: Use image node_id 1 to create a new ConvNetCifar10 object from inherited base classes: ConvNet with example: obj = ConvNetCifar10(nnObj, is_training, batch_norm_decay, batch_norm_epsilon, data_format)